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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

First Evaluation of the Climatological Calibration Algorithm in the Real-time TMPA Precipitation Estimates over Two Basins at High and Low Latitudes

The TRMM Multi-satellite Precipitation Analysis (TMPA) system underwent a crucial upgrade in early 2009 to include a climatological calibration algorithm (CCA) to its realtime product 3B42RT, and this algorithm will continue to be applied in the future Global Precipitation Measurement era constellation precipitation products. In this study, efforts are focused on the comparison and validation of the Version 6 3B42RT estimates before and after the climatological calibration is applied. The evaluation is accomplished using independent rain gauge networks located within the high-latitude Laohahe basin and the low-latitude Mishui basin, both in China. The analyses indicate the CCA can effectively reduce the systematic errors over the low-latitude Mishui basin but misrepresent the intensity distribution pattern of medium-high rain rates. This behavior could adversely affect TMPA's hydrological applications, especially for extreme events (e.g., floods and landslides). Results also show that the CCA tends to perform slightly worse, in particular, during summer and winter, over the high-latitude Laohahe basin. This is possibly due to the simplified calibration-processing scheme in the CCA that directly applies the climatological calibrators developed within 40 degrees latitude to the latitude belts of 40 degrees N-50 degrees N. Caution should therefore be exercised when using the calibrated 3B42RT for heavy rainfall-related flood forecasting (or landslide warning) over high-latitude regions, as the employment of the smooth-fill scheme in the CCA bias correction could homogenize the varying rainstorm characteristics. Finally, this study highlights that accurate detection and estimation of snow at high latitudes is still a challenging task for the future development of satellite precipitation retrievals.

TMPA-RT Precipitation Estimates↗
DOE OSTI2015

Challenge Online Time Series Clustering For Demand Response A Theory to Break the ‘Curse of Dimensionality'

The advent of smart meters and advanced communication infrastructures catalyzes numerous smart grid applications such as dynamic demand response, and paves the way to solve challenging research problems in sustainable energy consumption. The space of solution possibilities are restricted primarily by the huge amount of generated data requiring considerable computational resources and efficient algorithms. To overcome this Big Data challenge, data clustering techniques have been proposed. Current approaches however do not scale in the face of the “increasing dimensionality” problem where a cluster point is represented by the entire customer consumption time series. To overcome this aspect we first rethink the way cluster points are created and designed, and then design an efficient online clustering technique for demand response (DR) in order to analyze high volume, high dimensional energy consumption time series data at scale, and on the fly. Our online algorithm is randomized in nature, and provides optimal performance guarantees in a computationally efficient manner. Unlike prior work we (i) study the consumption properties of the whole population simultaneously rather than developing individual models for each customer separately, claiming it to be a ‘killer’ approach that breaks the “curse of dimensionality” in online time series clustering, and (ii) provide tight performance guarantees in theory to validate our approach. Our insights are driven by the field of sociology, where collective behavior often emerges as the result of individual patterns and lifestyles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Hydrogen Leak Modeling for Development of Smart Distributed Monitoring Under Unintended Releases

Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower. Hydrogen has the potential to play a crucial role in decarbonizing industrial processes that are currently reliant on fossil fuels and provide long-duration and/or seasonal energy storage to enable electricity decarbonization. Hydrogen can also be used as a fuel for fuel cell vehicles, providing a zero-emission alternative to traditional internal combustion engines. DOE launched the Hydrogen Energy Earthshot (Hydrogen Shot) in June 2021 to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). While promising, Hydrogen is highly-flammable, and in the presence of oxygen, it can form explosive mixtures. . Therefore, understanding leak scenarios is essential to evaluate and mitigate the safety risks associated with potential hydrogen leaks. An increased understanding of leak behavior, and having tools to model leaks, can help assess how hydrogen would disperse in different environments, influencing emergency response plans and safety measures, and identify potential issues with materials and design systems that can withstand the challenges posed by hydrogen. Recently, researchers have attempted to study hydrogen leaks for development of risk management strategies. However, the focus has been on closed or semi-closed spaces like storage rooms, vehicles, garages, and fueling stations - all promising locations for future hydrogen infrastructure. In this presentation, the modeling environment extends the span of research further by modeling hydrogen leak in an outdoor, open space. We will present the key challenges with modeling hydrogen leaks in an uncontrollable environment, how they were handled, and how modeling results informed sensor selection and placement. A Hydrogen research facility at the National Renewable Energy Laboratory (NREL) was used as a case study to model hydrogen leaks. In the future, Hydrogen wide area detection methodologies will be developed and tested at this site to monitor for unintended and operational hydrogen releases. The data generated from modeling will be used to develop a predictive model to detect hydrogen leak location based on concentration measured by sensors in this open space. Furthermore, the facility was also chosen because controlled hydrogen releases can be performed. A computational fluid dynamics (CFD) based modeling approach was taken to model hydrogen leak. The full-scale hydrogen facility was modeled with a large ambient domain. The electrolyzer at the facility can produce a controlled release rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind direction, wind speed at various altitudes, and temperature were used as inputs to the model. To capture the variability of weather conditions, a subset of the weather conditions experienced during daytime hours without precipitation over the course of three months was generated; using established data clustering techniques, a total of 100 condition sets were chosen. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. These distributions are compared to experimental data from a constant mass flow, controlled hydrogen release at the facility. The stochastic wind conditions of the release make direct validation difficult, therefore, statistical comparison approaches were used. Wind conditions are found to significantly impact the release behavior, including direction and concentration. Sensor selection and placement is proposed for the facility and is now based on release behavior predicted for the facility given its weather patterns; this is much more informed than without the modeling results. The methodology and analysis procedure can be translated to other facilities using modified geometries and site-specific weather conditions. Hydrogen holds great promise as a renewable energy fuel, but ensuring safety in its production, storage, and use is paramount. Studying potential leak scenarios in an open space will help develop sensors to detect hydrogen on a large spectrum of concentration and eventually build a smart distributed monitoring system.

CFD↗
DOE OSTI2015

Assessment of Edge Turbulence and Convective Transport through Velocity Field Analysis

Over the course of this grant period, we have conducted three major studies, each of which has resulted in a primary publication (described below): First, we investigated the flow and shear behavior of the edge plasma and scrape-off layer (SOL) in NSTX using the GPI diagnostic. Calculation of local, time resolved velocity maps using the hybrid optical flow and pattern matching velocimetry code enabled analysis of turbulent flow and shear behavior in these plasmas. Second, we used GPI measurements made during RF heated H-mode operation, to identify intermittent periodic edge intensity fluctuations which precede ELMs and ELM-induced back transitions from H-mode to Lmode. These edge oscillations have a well-defined mode structure and are visible up to 100-200 μs preceding the ELM events. Finally, we performed an in-depth investigation between the fluctuation measurements made by the GPI and BES diagnostics on NSTX.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Detecting Payload Attacks on Programmable Logic Controllers (PLCs)

Programmable logic controllers (PLCs) play critical roles in industrial control systems (ICS). Providing hardware peripherals and firmware support for control programs (i.e., a PLC’s “payload”) written in languages such as ladder logic, PLCs directly receive sensor readings and control ICS physical processes. An attacker with access to PLC development software (e.g., by compromising an engineering workstation) can modify the payload program and cause severe physical damages to the ICS. To protect critical ICS infrastructure, we propose to model runtime behaviors of legitimate PLC payload program and use runtime behavior monitoring in PLC firmware to detect payload attacks. By monitoring the I/O access patterns, network access patterns, as well as payload program timing characteristics, our proposed firmware-level detection mechanism can detect abnormal runtime behaviors of malicious PLC payload. Using our proof-of-concept implementation, we evaluate the memory and execution time overhead of implementing our proposed method and find that it is feasible to incorporate our method into existing PLC firmware. In addition, our evaluation results show that a wide variety of payload attacks can be effectively detected by our proposed approach. The proposed firmware-level payload attack detection scheme complements existing bumpin- the-wire solutions (e.g., external temporal-logic-based model checkers) in that it can detect payload attacks that violate realtime requirements of ICS operations and does not require any additional apparatus.

42 ENGINEERING↗
NASA NTRS1993

Formation and evolution of radial fracture systems on Venus

A survey of approximately 90 percent of the surface of Venus using Magellan data has been carried out to locate all radial fracture systems and to assess their association with other features such as volcanic edifices and coronae. Squyres et al. and Stofan et al. have discussed the association of radial fracture features in relation to coronae features, our approach was to assess the associations of all of the fracture systems. These fracture systems have two broad types of form - some fracture systems are associated with updomed topography, radiate from a point and have relatively uniform fracture lengths while others have a wider range of fracture lengths and radiate from the outer edge of a central caldera. Squyres et al. and Stofan et al. have interpreted both types of feature as reflecting tectonic fracturing resulting from uplift of the surface as a mantle plume impinges upon the crust. While it is true that a number of features are related to uplift and that such uplift will induce stresses consistent with radial fracturing, we explore the possibility that these fractures are not exclusively of tectonic origin. Purely tectonic fracturing will tend to generate a few main fractures/faults along which most of the stresses due to uplift will be accommodated leading to the triple-junction form common for terrestrial updoming. Though this type of feature is observed on Venus (e.g., feature located at 34S86), the majority of radial fracture systems display much more intensive fracturing than this through a full 360 degrees; this is difficult to explain by purely tectonic processes. The association of many of the fractures with radial lava flows leads us to interpret these fractures as reflecting dike emplacement: the form of the fractures being consistent with primarily vertical propagation from the head of a mantle plume. In the case of the second type of fracture system (those radiating from a central caldera), an even stronger case can be made that the fractures are not of tectonic origin. These features are not as commonly associated with updoming of the surface and where they are, the fractures extend out well beyond the edge of the topographic rise - an observation which is not consistent with the fractures being of tectonic uplift origin. Furthermore the fractures have a distribution of lengths (many short, fewer long) which is characteristic of dike swarms, and show direct associations with calderas and lava flows consistent with a volcanic origin. In addition, the longest fractures have a radial pattern only close to the center of the system but bend with distance to align themselves with the regional stress field - this behavior is very difficult to explain on purely tectonic grounds but is a pattern commonly seen for terrestrial dikes. For these reasons, we argue that many, if not the majority, of radial fracture systems found on Venus are the surface reflection of dike swarms, those associated with positive topography reflecting vertical emplacement and those radiating from calderas reflecting lateral propagation.

Parfitt, E. A.↗
DOE OSTI2023

TOWARDS RAPID RESPONSE UPDATES OF POPULATIONS AT RISK

Understanding population at risks has been a focus of the LandScan program through its development of population estimates. With advancements in computer vision, deep learning technologies and access to High Performance Computing (HPC) and high resolution imagery, population estimates are now modeled at the building level. However, when those patterns are disrupted, rapid updates to population distribution estimates are needed to support humanitarian aid and response. Oak Ridge National Laboratory (ORNL) recently adapted an existing deep learning building footprint extraction model in development of a scalable approach to Building Damage Assessments (BDA). This new opportunity opens the possibility of automating BDA to support rapid population distribution estimate updates for geographic areas involved in geopolitical conflicts or natural events for humanitarian aid and response or where to focus recovery efforts. In addition, incorporate social surveys to further model human behavior under conflict or other scenarios that disrupt normal patterns of life.

Urban, Marie↗
DOE OSTI2017

Visualizations of Travel Time Performance Based on Vehicle Reidentification Data

This paper provides a visual reference of the breadth of arterial performance phenomena based on travel time measures obtained from reidentification technology that has proliferated in the past 5 years. These graphical performance measures are revealed through overlay charts and statistical distribution as revealed through cumulative frequency diagrams (CFDs). With overlays of vehicle travel times from multiple days, dominant traffic patterns over a 24-h period are reinforced and reveal the traffic behavior induced primarily by the operation of traffic control at signalized intersections. A cumulative distribution function in the statistical literature provides a method for comparing traffic patterns from various time frames or locations in a compact visual format that provides intuitive feedback on arterial performance. The CFD may be accumulated hourly, by peak periods, or by time periods specific to signal timing plans that are in effect. Combined, overlay charts and CFDs provide visual tools with which to assess the quality and consistency of traffic movement for various periods throughout the day efficiently, without sacrificing detail, which is a typical byproduct of numeric-based performance measures. These methods are particularly effective for comparing before-and-after median travel times, as well as changes in interquartile range, to assess travel time reliability.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Four Beam Generation for Simultaneous Four-Hall Operation at CEBAF

As part of the CEBAF 12 GeV upgrade at Jefferson Lab, a new experimental hall was added to the existing three halls. To deliver beam to all four halls simultaneous-ly, a new timing pattern for electron bunches is needed at the injector. This pattern change has consequences for the frequency of the lasers at the photogun, beam behavior in the chopping system, beam optics due to space charge, and setup procedures. We have successfully demonstrated this new pattern using the three existing drive lasers. The implementation of the full system will occur when the fourth laser is added and upgrades to the Low Level RF (LLRF) are complete. In this paper we explain the new bunch pattern, the challenges for setting and measuring the pattern such as 180° RF phase ambiguity, addition of the fourth laser to the laser table and LLRF upgrade.

Kazimi, Reza↗
NASA NTRS2011

Wave Forcing of Saturn's Equatorial Oscillation

Ground-based measurements and Cassini data from CIRS thermal-infrared spectra and radio-occultation soundings have characterized the spatial structure and temporal behavior of a 15-year equatorial oscillation in Saturn's stratosphere. The equatorial region displays a vertical pattern of alternating warm and cold anomalies and, concomitantly, easterly and westerly winds relative to the cloud-top winds, with a peak-to-peak amplitude of 200 m/s. Comparison of the Cassini data over a four-year period has established that the pattern of mean zonal winds and temperatures descends at a rate of roughly I scale height over 4 years. This behavior is reminiscent of the equatorial oscillations in Earth's middle atmosphere. Here the zonal-mean spatial structure and descending pattern are driven by the absorption of vertically propagating waves. The maximum excursions in the pattern of easterly and westerly winds is determined by the limits of the zonal phase velocities of the waves. Here we report on the characterization of the waves seen in the temperature profiles retrieved from the Cassini radio-occultation soundings. The equatorial profiles exhibit a complex pattern of wavelike structure with dimensions one pressure scale height and smaller. We combine a spectral decomposition with a WKBJ analysis, where the vertical wavelength is assumed to vary slowly with the ambient static stability and doppler-shifted phase velocity of the wave. Use of the temperature and zonal wind maps from CIRS makes this approach viable. On Earth, the wave forcing associated with the equatorial oscillations generates secondary meridional circulations that affect the mean flow and planetary wave ducting well away from the equator. This may relate to the triggering of the recently reported mid-latitude storms on Saturn.

Flasar, F. M.↗
DOE OSTI2020

Unusual Breathing Behavior of Optically Excited Barium Titanate Nanocrystals

Coherent X-ray diffraction patterns were recorded by using an X-ray free-electron laser to illuminate barium titanate nanocrystals as a function of time delay after laser excitation. Rather than seeing any significant thermal expansion effects, the diffraction peaks were found to move perpendicular to the momentum transfer direction. This suggests a laser driven rotation of the crystal lattice, which is delayed by the aggregated state of the crystals. Internal deformations associated with crystal contacts were also observed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2008

Chromium and Tantalum Site Substitution Patterns in Ni3Al (L1(sub 2))gamma(prime)- Precipitates

The site substitution behavior of Cr and Ta in the Ni3Al (Ll2)-type gamma'-precipitates of a Ni-Al-Cr-Ta alloy is investigated by atom-probe tomography (APT) and first-principles calculations. Measurements of the gamma'-phase composition by APT suggest that Al, Cr, and Ta share the Al sublattice sites of the gamma'-precipitates. The calculated substitutional energies of the solute atoms at the Ni and Al sublattice sites indicate that Ta has a strong preference for the Al sites, while Cr has a weak Al site preference. Furthermore, Ta is shown to replace Cr at the Al sublattice sites of the gamma'-precipitates, altering the elemental phase partitioning behavior of the Ni-Al-Cr-Ta alloy.

Booth-Morrison, Christopher↗
DOE OSTI2014

ERK Oscillation-Dependent Gene Expression Patterns and Deregulation by Stress-Response

Studies were undertaken to determine whether ERK oscillations regulate a unique subset of genes in human keratinocytes and subsequently, whether the p38 stress response inhibits ERK oscillations. A DNA microarray identified many genes that were unique to ERK oscillations, and network reconstruction predicted an important role for the mediator complex subunit 1 (MED1) node in mediating ERK oscillation-dependent gene expression. Increased ERK-dependent phosphorylation of MED1 was observed in oscillating cells compared to non-oscillating counterparts as validation. Treatment of keratinocytes with a p38 inhibitor (SB203580) increased ERK oscillation amplitudes and MED1 and phospho-MED1 protein levels. Bromate is a probable human carcinogen that activates p38. Bromate inhibited ERK oscillations in human keratinocytes and JB6 cells and induced an increase in phospho-p38 and decrease in phospho-MED1 protein levels. Treatment of normal rat kidney cells and primary salivary gland epithelial cells with bromate decreased phospho-MED1 levels in a reversible fashion upon treatment with p38 inhibitors (SB202190; SB203580). Our results indicate that oscillatory behavior in the ERK pathway alters homeostatic gene regulation patterns and that the cellular response to perturbation may manifest differently in oscillating vs non-oscillating cells.

carcinogenesis↗
NASA NTRS2013

Data Mining for Understanding and Impriving Decision-Making Affecting Ground Delay Programs

The continuous growth in the demand for air transportation results in an imbalance between airspace capacity and traffic demand. The airspace capacity of a region depends on the ability of the system to maintain safe separation between aircraft in the region. In addition to growing demand, the airspace capacity is severely limited by convective weather. During such conditions, traffic managers at the FAA's Air Traffic Control System Command Center (ATCSCC) and dispatchers at various Airlines' Operations Center (AOC) collaborate to mitigate the demand-capacity imbalance caused by weather. The end result is the implementation of a set of Traffic Flow Management (TFM) initiatives such as ground delay programs, reroute advisories, flow metering, and ground stops. Data Mining is the automated process of analyzing large sets of data and then extracting patterns in the data. Data mining tools are capable of predicting behaviors and future trends, allowing an organization to benefit from past experience in making knowledge-driven decisions. The work reported in this paper is focused on ground delay programs. Data mining algorithms have the potential to develop associations between weather patterns and the corresponding ground delay program responses. If successful, they can be used to improve and standardize TFM decision resulting in better predictability of traffic flows on days with reliable weather forecasts. The approach here seeks to develop a set of data mining and machine learning models and apply them to historical archives of weather observations and forecasts and TFM initiatives to determine the extent to which the theory can predict and explain the observed traffic flow behaviors.

data mining↗
DOE OSTI2014

Initial value predictability of intrinsic oceanic modes and implications for decadal prediction over North America

The overall aim of our project was to quantify and characterize predictability of the climate as it pertains to decadal time scale predictions. By predictability we mean the degree to which a climate forecast can be distinguished from the climate that exists at initial forecast time, taking into consideration the growth of uncertainty that occurs as a result of the climate system being chaotic. In our project we were especially interested in predictability that arises from initializing forecasts from some specific state though we also contrast this predictability with predictability arising from forecasting the reaction of the system to external forcing – for example changes in greenhouse gas concentration. Also, we put special emphasis on the predictability of prominent intrinsic patterns of the system because they often dominate system behavior. Highlights from this work include: • Development of novel methods for estimating the predictability of climate forecast models. • Quantification of the initial value predictability limits of ocean heat content and the overturning circulation in the Atlantic as they are represented in various state of the art climate models. These limits varied substantially from model to model but on average were about a decade with North Atlantic heat content tending to be more predictable than North Pacific heat content. • Comparison of predictability resulting from knowledge of the current state of the climate system with predictability resulting from estimates of how the climate system will react to changes in greenhouse gas concentrations. It turned out that knowledge of the initial state produces a larger impact on forecasts for the first 5 to 10 years of projections. • Estimation of the predictability of dominant patterns of ocean variability including well-known patterns of variability in the North Pacific and North Atlantic. For the most part these patterns were predictable for 5 to 10 years. • Determination of especially predictable patterns in the North Atlantic. The most predictable of these retain predictability substantially longer than generic patterns, with some being predictable for two decades.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Quantifying the local adaptive landscape of a nascent bacterial community

Abstract The fitness effects of all possible mutations available to an organism largely shape the dynamics of evolutionary adaptation. Yet, whether and how this adaptive landscape changes over evolutionary times, especially upon ecological diversification and changes in community composition, remains poorly understood. We sought to fill this gap by analyzing a stable community of two closely related ecotypes (“L” and “S”) shortly after they emerged within the E. coli Long-Term Evolution Experiment (LTEE). We engineered genome-wide barcoded transposon libraries to measure the invasion fitness effects of all possible gene knockouts in the coexisting strains as well as their ancestor, for many different, ecologically relevant conditions. We find consistent statistical patterns of fitness effect variation across both genetic background and community composition, despite the idiosyncratic behavior of individual knockouts. Additionally, fitness effects are correlated with evolutionary outcomes for a number of conditions, possibly revealing shifting patterns of adaptation. Together, our results reveal how ecological and epistatic effects combine to shape the adaptive landscape in a nascent ecological community.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1998

Multi-Scale Fractal Analysis of Image Texture and Pattern

Fractals embody important ideas of self-similarity, in which the spatial behavior or appearance of a system is largely independent of scale. Self-similarity is defined as a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. An ideal fractal (or monofractal) curve or surface has a constant dimension over all scales, although it may not be an integer value. This is in contrast to Euclidean or topological dimensions, where discrete one, two, and three dimensions describe curves, planes, and volumes. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution. However, most geographical phenomena are not strictly self-similar at all scales, but they can often be modeled by a stochastic fractal in which the scaling and self-similarity properties of the fractal have inexact patterns that can be described by statistics. Stochastic fractal sets relax the monofractal self-similarity assumption and measure many scales and resolutions in order to represent the varying form of a phenomenon as a function of local variables across space. In image interpretation, pattern is defined as the overall spatial form of related features, and the repetition of certain forms is a characteristic pattern found in many cultural objects and some natural features. Texture is the visual impression of coarseness or smoothness caused by the variability or uniformity of image tone or color. A potential use of fractals concerns the analysis of image texture. In these situations it is commonly observed that the degree of roughness or inexactness in an image or surface is a function of scale and not of experimental technique. The fractal dimension of remote sensing data could yield quantitative insight on the spatial complexity and information content contained within these data. A software package known as the Image Characterization and Modeling System (ICAMS) was used to explore how fractal dimension is related to surface texture and pattern. The ICAMS software was verified using simulated images of ideal fractal surfaces with specified dimensions. The fractal dimension for areas of homogeneous land cover in the vicinity of Huntsville, Alabama was measured to investigate the relationship between texture and resolution for different land covers.

Emerson, Charles W.↗
DOE OSTI2018

Magnetosphere dynamics during the 14 November 2012 storm inferred from TWINS, AMPERE, Van Allen Probes, and BATS-R-US–CRCM

During the 14 November 2012 geomagnetic storm, the Van Allen Probes spacecraft observed a number of sharp decreases ("dropouts") in particle fluxes for ions and electrons of different energies. In this paper, we investigate the global magnetosphere dynamics and magnetosphere–ionosphere (M–I) coupling during the dropout events using multipoint measurements by Van Allen Probes, TWINS, and AMPERE together with the output of the two-way coupled global BATS-R-US–CRCM model. We find different behavior for two pairs of dropouts. For one pair, the same pattern was repeated: (1) weak nightside Region 1 and 2 Birkeland currents before and during the dropout; (2) intensification of Region 2 currents after the dropout; and (3) a particle injection detected by TWINS after the dropout. The model predicted similar behavior of Birkeland currents. TWINS low-altitude emissions demonstrated high variability during these intervals, indicating high geomagnetic activity in the near-Earth tail region. For the second pair of dropouts, the structure of both Birkeland currents and ENA emissions was relatively stable. The model also showed quasi-stationary behavior of Birkeland currents and simulated ENA emissions with gradual ring current buildup. We confirm that the first pair of dropouts was caused by large-scale motions of the OCB (open–closed boundary) during substorm activity. We show the new result that this OCB motion was associated with global changes in Birkeland (M–I coupling) currents and strong modulation of low-altitude ion precipitation. The second pair of dropouts is the result of smaller OCB disturbances not related to magnetospheric substorms. The local observations of the first pair of dropouts result from a global magnetospheric reconfiguration, which is manifested by ion injections and enhanced ion precipitation detected by TWINS and changes in the structure of Birkeland currents detected by AMPERE. This study demonstrates that multipoint measurements along with the global model results enable the reconstruction of a more complete system-level picture of the dropout events and provides insight into M–I coupling aspects that have not previously been investigated.

79 ASTRONOMY AND ASTROPHYSICS↗